P1074
Building National Platforms and International Networks to Tackle the Phenotyping Bottleneck

Date: Monday, January 13, 2014
Room: Grand Exhibit Hall
Niklas Körber , Forschungszentrum Jülich GmbH, Jülich, Germany
Adolf Keßeler , Forschungszentrum Jülich GmbH, Jülich, Germany
Roland Pieruschka , Forschungszentrum Jülich GmbH, Jülich, Germany
Fabio Fiorani , Forschungszentrum Jülich GmbH, Jülich, Germany
Ulrich Schurr , Forschungszentrum Jülich GmbH, Jülich, Germany
Plants are at the center of future grand challenges to mitigate the impact of climate change and guarantee sufficient food, feed and renewable resources. Integrating approaches across all scales of plant systems from molecular to field applications are necessary to develop sustainable plant production in the future. In recent years molecular and genetic tools realized significant progress towards improvement of plant breeding pipelines. However, the ability to phenotype plants at different scales and identify which traits are heritable, still remains a bottleneck.

Measuring systematically and at high-throughput plant phenotypes under defined environmental conditions in the lab and in target environments in the field is a key requirement to bridge the gap between genome and phenome.  At the Institute of Plant Sciences (Forschungszentrum Juelich), we lead significant projects to increase the capacity for using minimally invasive phenotyping for screening and mechanistic understanding of phenotype x environment interactions. The European Plant Phenotyping Network (EPPN; http://www.plant-phenotyping-network.eu/) aims at making use of the current European phenotyping platforms for whole plant and molecular profiling by offering transnational access to the participating platforms. Additionally, the German Plant Phenotyping Network (DPPN; (http://www.dppn.de/dppn/EN/Home) will develop new methods and infrastructure to determine plants the phenotypes and GxE interactions of, tolerance to abiotic stress or the concentration of important metabolites or precursors. To fully address these questions, most of these methods are non-invasive allow in-vivo as well as quantitative measurements. Furthermore, automated data processing and database development is a key development to interpret the large and multi-dimensional data sets.